Home Media Razorthink Launches the First of its Kind Deep Learning Data Science Automation...

Razorthink Launches the First of its Kind Deep Learning Data Science Automation Platform

Razorthink Big Brain marks the first Deep Learning Data Science Platform to be launched by Razorthink Inc., which is an innovator in Artificial Intelligence Data Science for the Enterprise.

The platform aids in automating the data preparation, evaluation, modeling and deploying of the Deep Learning solutions at the required size. Additionally, it will assist organizations and businesses in generating Expert AIs rapidly and avert blind spots.

Big Brain platform produces optimized and customized Expert AIs primarily meant for businesses cases like fraud detection, credit risk, customer engagement, targeted marketing and wealth management.

A press release by Gartner, dated January 16, 2017, forecasts the automation of over 40 percent of data science activities by 2020. The outcome of the situation will be access to additional data sources.

Additionally, Gary Oliver, the chairperson and CEO of Razorthink, acknowledged the disruption of technology in almost all industries.

The banking industry is also at a critical stage, which is owed to tech giants and Fintech start-ups delivering new financial products that revolve around digital banking convenience. Nonetheless, applying Deep Learning to big data can help the traditional banking firms acquire a competitive advantage.

According to Axis Bank’s head of business and EVP, Balaji Narayanamurthy, Razorthink is among the few successful players in the analytics prediction field.

He added that the company has been assisting Axis Bank in predicting client behavior more accurately. For this reason, financial service firm intends to utilize Razorthink Big Brain within the bank, especially in solving more complicated issues.

The Razorthink platform utilizes five components to automate data modeling, evaluating preparation and distribution of Deep Learning solutions. They include:

• Data Optimizer- Refines and wrangles raw data to automate the process of data transformation.

• Deep Learning Modeler – Enables the users to not only create but also edit hybrid unsupervised and supervised models through its drag and drop interface.

• Model Optimizer – It allows the creation of run templates mainly for model execution and assists in viewing and comparing model run results

• Deployment Optimizer – Guides the users on how to carry out Expert AI configuration according to the number of software and servers required.

• Big Brain Communicator – It exhibits the models built alongside the details of the process of their creation.

Original source Razorthink

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KC Cheung
KC Cheung
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
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